An Appropriate Method Ranking Approach for Localizing Bugs using Minimized Search Space

Shanto Rahman, Kazi Sakib

Abstract

In automatic software bug localization, source code analysis is usually used to localize the buggy code without manual intervention. However, due to considering irrelevant source code, localization accuracy may get biased. In this paper, a Method level Bug localization using Minimized search space (MBuM) is proposed for improving the accuracy, which considers only the liable source code for generating a bug. The relevant search space for a bug is extracted using the execution trace of the source code. By processing these relevant source code and the bug report, code and bug corpora are generated. Afterwards, MBuM ranks the source code methods based on the textual similarity between the bug and code corpora. To do so, modified Vector Space Model (mVSM) is used which incorporates the size of a method with Vector Space Model. Rigorous experimental analysis using different case studies are conducted on two large scale open source projects namely Eclipse and Mozilla. Experiments show that MBuM outperforms existing bug localization techniques.

References

  1. Deerwester, S. C., Dumais, S. T., Landauer, T. K., Furnas, G. W., and Harshman, R. A. (1990). Indexing by latent semantic analysis. JAsIs, 41(6):391-407.
  2. Eisenbarth, T., Koschke, R., and Simon, D. (2003). Locating features in source code. IEEE Transactions on Software Engineering, 29(3):210-224.
  3. Frakes, W.B.(1992). Stemming algorithms. pages 131-160.
  4. Kim, D., Tao, Y., Kim, S., and Zeller, A. (2013). Where should we fix this bug? a two-phase recommendation model. IEEE Transactions on Software Engineering, 39(11):1597-1610.
  5. Lukins, S. K., Kraft, N., Etzkorn, L. H., et al. (2008). Source code retrieval for bug localization using latent dirichlet allocation. In 15th Working Conference on Reverse Engineering, (WCRE), pages 155-164. IEEE.
  6. Nguyen, A. T., Nguyen, T. T., Al-Kofahi, J., Nguyen, H. V., and Nguyen, T. N. (2011). A topic-based approach for narrowing the search space of buggy files from a bug report. In Automated Software Engineering (ASE), 26th IEEE/ACM International Conference on, pages 263-272. IEEE.
  7. Nichols, B. D. (2010). Augmented bug localization using past bug information. In 48th Annual Southeast Regional Conference, page 61. ACM.
  8. Poshyvanyk, D., Gueheneuc, Y.-G., Marcus, A., Antoniol, G., and Rajlich, V. C. (2007). Feature location using probabilistic ranking of methods based on execution scenarios and information retrieval. IEEE Transactions on Software Engineering, 33(6):420-432.
  9. Rahman, S. (4/1/2016). shanto-rahman/mbum: 2016. https://github.com/shanto-Rahman/MBuM.
  10. Rahman, S., Ganguly, K., and Kazi, S. (2015). An improved bug localization using structured information retrieval and version history. In 18th International Conference on Computer and Information Technology (ICCIT).
  11. Saha, R. K., Lease, M., Khurshid, S., and Perry, D. E. (2013). Improving bug localization using structured information retrieval. In 28th International Conference on Automated Software Engineering (ASE, 2013), pages 345-355. IEEE.
  12. Wang, S. and Lo, D. (2014). Version history, similar report, and structure: Putting them together for improved bug localization. In 22nd International Conference on Program Comprehension, pages 53-63. ACM.
  13. Zhou, J., Zhang, H., and Lo, D. (2012). Where should the bugs be fixed? more accurate information retrievalbased bug localization based on bug reports. In 34th International Conference on Software Engineering (ICSE), pages 14-24. IEEE.
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Paper Citation


in Harvard Style

Rahman S. and Sakib K. (2016). An Appropriate Method Ranking Approach for Localizing Bugs using Minimized Search Space . In Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-189-2, pages 303-309. DOI: 10.5220/0005896403030309


in Bibtex Style

@conference{enase16,
author={Shanto Rahman and Kazi Sakib},
title={An Appropriate Method Ranking Approach for Localizing Bugs using Minimized Search Space},
booktitle={Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE,},
year={2016},
pages={303-309},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005896403030309},
isbn={978-989-758-189-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE,
TI - An Appropriate Method Ranking Approach for Localizing Bugs using Minimized Search Space
SN - 978-989-758-189-2
AU - Rahman S.
AU - Sakib K.
PY - 2016
SP - 303
EP - 309
DO - 10.5220/0005896403030309